code: def test_mantis_mask_rcnn_predict(
      sample_dataset, pretrained_state_dict
  ):
      model = mask_rcnn.model(num_classes=91)
      model.load_state_dict(pretrained_state_dict)
  
      preds = mask_rcnn.predict(model=model, dataset=sample_dataset)
      _test_preds(preds)
  
file_path: icevision/tests/models/torchvision_models/mask_rcnn/test_predict.py
imports: import pytest
  from icevision.imports import *
  from icevision import *
  from icevision.models.torchvision import mask_rcnn
label_desc: Use image node_id 4 for calling a global function with example usage: test_mantis_mask_rcnn_predict(sample_dataset, pretrained_state_dict) without return types